The power generation amount of a photovoltaic power generation system is susceptible to solar radiation and is unstable, and therefore, attention is paid to an apparatus that predicts a short-term power generation amount. Concerning the short-term power generation prediction of a photovoltaic power generation system, the following method is known. The method is for predicting a power generation amount by performing short-term prediction of a solar radiation value of a prediction target time by using a regression model from meteorological forecast data in a range of the prediction target time from a certain time, and solar radiation value time series up to the time. As the regression model, a linear model, a neural net and the like can be used. Further, the method of Japanese Patent Application No. 2009-29211 estimates a situation of clouds from a power generation situation at a certain time, and performs short-term power generation amount prediction by using spatial information. However, as the cloud situation, processing as three-dimensional spatial information is not described.
According to the technique using the regression model described above, it can be expected that prediction with accuracy to some degree is enabled by combining a meteorological prediction result which is estimated from various meteorological data and actual power generation data. However, the meteorological conditions vary depending on the installation situations of photovoltaic power generation systems, seasons and time zones, and construction of a regression model which is compatible with any situation is difficult. Therefore, there arises the problem that the prediction accuracy is limited. Further, according to the technique of Japanese Patent Application No. 2009-29211 described above, it can be expected that prediction of a power generation amount by using spatial information such as clouds is enabled. However, in the movements of clouds, movements in a vertical direction and a horizontal direction of a cirrus cloud, a cumulus cloud and the like have to be considered. Therefore, there arises the problem that accurate estimation of a cloud situation and power generation amount prediction are difficult unless three-dimensional spatial information cannot be dealt with.